what works in behaviour change? 28 june 2010, victoria quay, edinburgh

Who responds to smarter measures? Lessons from the Sustainable Travel Towns in England and Scotland.What Works in Behaviour Change? 28 June 2010, Victoria Quay, EdinburghDr Jillian Anable: The Centre for Transport Research, University of AberdeenLynn Sloman, Carey Newson: Transport for Quality of LifeSally Cairns: Transport Research LaboratoryPhil Goodwin: University West of EnglandDerek Halden: DHC Ltd

What are Smart Choices?techniques for influencing travel behaviour towards more sustainable optionssometimes called soft measuresmore psychology than engineering engage with people about their travel choicesmay involve:better information about existing travel optionsmarketing and communicationnew transport services, closely focussed on target marketcarrots and sticks, working together

How we Get Smarter

QuestionsHow effective are smarter choices?Who responds to smarter choices?What are the ingredients that influence effectiveness?What are the psychological processes that lead to travel behaviour change?How can these processes be tapped more effectively?

Scepticism about Smarter MeasuresCherry picked evidence?Unscientific monitoring and evaluation?Behaviour change is just short term?Preaching to the converted?Only has an impact on short journeys?Widens health inequalities?

After two large-scale demonstration studies, what will we learn?

Sustainable Travel Towns: England10m from DfT (2004-2009)

STTs: balance of measures (revenue)Workplace travel planningTravel awareness campaignsSchool travel planningCycling and walking promotionPersonal travel planningCar clubPublic transport info & marketingDarlingtonWorcesterPeterborough

Chart8

0.0387282634

0.0371865592

0.4105853905

0.1055689266

0.2398433466

0.1680875137

0

Peterborough

Peterborough

data source: strategic write-up latest version as at 18.10.08

2004/052005/062006/072007/082008/09TOTALSMART MEASURES PER CENT

Smart measurecapitalnon-staff revenue costsstaff costscapitalnon-staff revenue costsstaff costscapitalnon-staff revenue costsStaff costscapitalnon-staff revenue costsstaff costscapitalnon-staff revenue costsstaff costscapitalnon-staff revenue costsstaff costscapitalnon-staff revenue costsstaff costs

WTPBusiness travel planning012,85607,574019,276016,423012,50006862900%4%Non-staff revenue

STPSchool travel planning315,1116,976159,70212,407235,01215,793150,70516,221150,00014,500101053065897044%4%WTP4%

PTPIndividualised travel marketing05,2250225,5000210,5270286,33200072758400%41%STP4%

PTIMReal time passenger information0104219,5006,832140,75132,322130,98639,93250,00020,00054123799190024%6%PTP41%

PTIMPassenger information screens0080,1500000005,00080150500003%0%PTIM11%

PTIMInteractive kiosks07,052012,55908,371011,14705,00004412900%2%TA24%

PTIMTravel information centre0046,983000017,756016,000469833375602%2%CW17%

PTIMSustainable transport interchange info0016,650011,203010,931005,00038784500002%0%100%

TASmartcard01,73003,59401,64409,42207,00002339000%1%

TAInteractive website020048,3666,85003203,73515,0005,000633661581703%1%Capital

TAInteractive map0020,285008,22807,10005,000202852032801%1%WTP0%

TAIntegrated sustainable transport guide00037,94309,235021,195010,00007837300%4%STP44%

TAMarketing and promotion039,962097,418048,703091,027010,000028711000%16%PTP0%

CWWalking and safety0030,45912,420021,8424,5153,27755,0003,000899744053904%2%PTIM31%

CWMore Cycling048,87786,44150,67096,02132,77823,95170,806170,00014,000376413217131016%12%TA4%

CWRoute branding005,00030,58116,4889131,2733,19805,500227614019201%2%CW21%

Research and evaluation0118,183034,347021,250012,1530115,20003011330100%

Other schemes0000098,0860-16,611000814750

Salaries0125,8210237,8760230,0820219,8440251,638001065261Smart measures cap:rev ratio

Accomm (Integ Transportation Unit)070,000085,077068,824040,000045,00003089010Capital56%

Misc (equip/training/admin etc)013,377022,54306,962014,097000569790Revenue44%

TOTAL315,111324,542125,821713,535646,313237,876499,475604,787230,082322,363647,209219,844440,000297,700251,638229048425205511065261

Total cap:rev ratio

TOTAL for smart measures*31511112298207135365043480499475409664032236159757104400001375000229048317720650100%100%0%Capital39%

Revenue61%

* excludes research, salaries, accommodation, other schemes, miscellaneous

This only includes capital schemes specifically identified by the towns as part of their smarter choices work. There are other capital schemes (e.g. relating to general public transport improvements) which are not included in these figures

only for expenditure directly related to a specific smart measure i.e. excludes research, salaries, accommodation, other schemes, miscellaneous

includes all expenditure, identified by town as part of its STT programme, whether directly related to a specific smart measure or not

Worcester

data source: paper 2 submitted to DfT dated 16 Sept 2008


(projected)

Smart measureNon-staff revenue costsStaff costsNon-staff revenue costsStaff costsNon-staff revenue costsStaff costsNon-staff revenue costsStaff costsNon-staff revenue costsStaff costsNon-staff revenue costsStaff costsNon-staff revenue costsStaff costs

PMProject management (includes research costs)112,300134,000108,500270,00010,000271,00066,000218,000142,500250,500439,3001,143,500Non-staff revenue

WTPWorkplace travel planning12,50020,00010,00020,00062,50005%WTP9%

STPSchool travel planning11,0003,0004,0005,00023,00002%STP2%

PTPPersonal travel planning135,00098,225157,000390,225033%PTP33%

PTIMPublic transport information & marketing25,00016,00020,00010,00071,00006%PTIM6%

TATravel awareness campaigns (not mode-specific)41,71742,50016,00037,40025,000162,617014%TA14%

CWInformation, marketing and events specifically to promote walking10,00017,50018,70010,00056,20005%CW23%

CWInformation, marketing and events specifically to promote cycling*30,00015,50083,00088,000216,500018%CC14%

CCCar clubs80,00080,000160,000014%100%

WTP / CSCar-sharing scheme30,00010,00040,00003%

Traffic management support35,00035,0000

TOTAL:165,017134,000398,500270,000276,225271,000506,100218,000310,500250,5001,656,3421,143,500

TOTAL for smart measures*52,7170255,0000266,2250440,1000168,00001,182,0420100%

*excludes project management, research, traffic management support

Darlington


Smart measurecapitalNon-staff revenue costsStaff costscapitalNon-staff revenue costsStaff costscapitalNon-staff revenue costsStaff costscapitalNon-staff revenue costsStaff costscapitalNon-staff revenue costsStaff costscapitalNon-staff revenue costsStaff costscapitalNon-staff revenue costsStaff costsNon-staff revenuenon-staff revenue plus allocated staff costsStaff costs related to specific smart measures

Overall project management44,00018,00058,00046,00050,00051,000018000249000WTP1.5%4%WTP11%

Workplace travel planning7,5003,0008,0005,0008,0005,00012,0005,00021,000018000565000%1%11%STP5%9%STP25%

School travel planning2,00024,0005,00025,00020,00026,00035,00027,00035,00028,0000970001300000%5%25%PTP46%36%PTP0%

Personal travel planning83,000257,200293,779235,500086947900%46%0%PTIM5%7%PTIM13%

PTIM10,0008,50070,00020,00014,00020,00014,50030,00015,00020,00015,0007000010000067000100%5%13%TA28%25%TA17%

General travel awareness50,0002,500140,00014,000140,00022,000100,00023,00090,00024,0000520000855000%28%17%CW15%19%CW34%

W&C information and events10,00020,00015,00015,00020,00015,00020,00015,00020,00015,000085000800000%4%16%100.0%100.0%100%

Cycle and pedestrian training10,00010,00041,00020,00070,00021,00070,00022,00023,0000191000960000%10%19%

Car sharing1,5001,5001,5003,5002,00001000000%1%0%

Overall media management / PR1,5002,5002,0005,0004,5006,0005,0006,0005,0006,00001800025500CapitalSmart measures cap:rev ratio

Internal communications250500500500500022500WTPcapital4%

Monitoring (in-house)75,000200020,0002,00028,0002,00029,0002,10030,0002,10031,0007500010200138000STPrevenue96%

Travel research (Social data)112,00033,50033,50033,500120,00003325000PTP

PTIM100%

TOTAL75,000282,250139,00070,000538,700187,0000610,779187,5000540,100200,0000299,600214,0001450002271429927500TA

CW

TOTAL for smart measures*0166500725007000048270096000057027910650004990001140000172000126000700001890479515000100%100%100%

* excludes overall project management, media management /PR, internal comms, monitoring (in house), travel research (Socialdata), salaries

only for expenditure directly related to a specific smart measure i.e. excludes research, project management, media management, internal comms, monitoring. Also excludes all salaries.

Revenue summary

Non-staff revenue allocated to specific smart measures

PeterboroughWorcesterDarlingtonDarlington with some staff costs allocated

workplace travel planning4%9%1%4%

school travel planning4%2%5%9%

personal travel planning41%33%46%36%

public transport info & marketing11%6%5%7%

travel awareness campaigns24%14%28%25%

cycling & walking promotion17%23%15%19%

car clubs0%14%0%0%

revenue spend

allocated to specific smart measures1,772,0651,182,0421890479

staff costs1,065,2611,143,500927500

other costs748,488474,300380950

total3,585,8142,799,8423,198,929

49%42%59%

Revenue summary

Peterborough

Worcester

allocated to specific smart measures

staff costs

other costs

Revenue spend over 5 years

Darlington

Darlington with some staff costs allocated

Chart9

0.0867143469

0.0194578534

0.3301278635

0.0600655476

0.1375729458

0.2307024623

0.1353589805

Worcester

Peterborough












TASmartcard01,73003,59401,64409,42207,00002339000%1%









Other schemes0000098,0860-16,611000814750




TOTAL315,111324,542125,821713,535646,313237,876499,475604,787230,082322,363647,209219,844440,000297,700251,638229048425205511065261

Total cap:rev ratio


Revenue61%





Worcester



(projected)










CCCar clubs80,00080,000160,000014%100%



TOTAL:165,017134,000398,500270,000276,225271,000506,100218,000310,500250,5001,656,3421,143,500



Darlington







PTIM10,0008,50070,00020,00014,00020,00014,50030,00015,00020,00015,0007000010000067000100%5%13%TA28%25%TA17%




Car sharing1,5001,5001,5003,5002,00001000000%1%0%





PTIM100%

TOTAL75,000282,250139,00070,000538,700187,0000610,779187,5000540,100200,0000299,600214,0001450002271429927500TA

CW




Revenue summary









car clubs0%14%0%0%

revenue spend


staff costs1,065,2611,143,500927500

other costs748,488474,300380950

total3,585,8142,799,8423,198,929

49%42%59%

Revenue summary

Peterborough

Worcester


staff costs

other costs


Darlington


Chart10

0.0148110611

0.0513097474

0.4599252359

0.0528966468

0.2750625635

0.1459947452

0

Darlington

Peterborough












TASmartcard01,73003,59401,64409,42207,00002339000%1%









Other schemes0000098,0860-16,611000814750




TOTAL315,111324,542125,821713,535646,313237,876499,475604,787230,082322,363647,209219,844440,000297,700251,638229048425205511065261

Total cap:rev ratio


Revenue61%





Worcester



(projected)










CCCar clubs80,00080,000160,000014%100%



TOTAL:165,017134,000398,500270,000276,225271,000506,100218,000310,500250,5001,656,3421,143,500



Darlington







PTIM10,0008,50070,00020,00014,00020,00014,50030,00015,00020,00015,0007000010000067000100%5%13%TA28%25%TA17%




Car sharing1,5001,5001,5003,5002,00001000000%1%0%





PTIM100%

TOTAL75,000282,250139,00070,000538,700187,0000610,779187,5000540,100200,0000299,600214,0001450002271429927500TA

CW




Revenue summary









car clubs0%14%0%0%

revenue spend


staff costs1,065,2611,143,500927500

other costs748,488474,300380950

total3,585,8142,799,8423,198,929

49%42%59%

Revenue summary

Peterborough

Worcester


staff costs

other costs


Darlington


Smarter Choices, Smarter Places: Scotland15m from SG (2008-2011)

Larbert/Stenhousemuir Rebuild bus use Encourage walking and cycling for work and shopping trips to the town centre Improve local cycling facilitiesBarrhead New paths in Auchenback and links to Darnley Country Park Develop local cycle culture Improve image of bus travel Develop safer routes to schoolsKirkintilloch/Lenzie High street information centre Events promoting walking and cycling Workplace and school travel planningKirkwall Improve walking environment in the town centre and Quoybanks Maintain strong cycle culture Promote bus use including travel training and tourist informationDumfries Persuade drivers to walk more for short trips Improve bus routes and ticketing Link existing cycle routes to town centre Park and choose schemesDundee Market bus use to build on existing high levels Reinforce health benefits of cycling through work with schools and families Make bicycles available through loan schemesGlasgow East End Improvements to three key walking and cycling corridors Personalised travel planning Address local safety concerns

STTs: data sourcesHousehold travel survey (undertaken 2004 & 2008, 4000 people each town each survey)Counts of:VehiclesCyclistsPedestriansBus passengers

School and workplace surveysNational Travel Survey medium-sized urban areas

National Road Traffic Estimates urban roadsTown DataNational Data

Household surveys changes in tripsAll tripsCar driverCar passengerBusCycleWalkChange in trip numbers per 100 people per day 2004 to 2008; weighted dataset; trips

Outcomes: comparing car travel from surveys with traffic / car countsHousehold surveysTraffic / car counts

Trips per personDistance per personNational trend-1.2%-0.9%

Sustainable Travel Towns-9%-5%~-7%Darlington-7%~-10%-6%~-7%Peterborough-8%~-10%-7%~10%Worcester-8%~-10%-3%

Inner areaOuter areaOverall change-0.5% (car)or -0.7% (all)

-6.7% to -5.3%+1.6% to -0.2%-2.4% to -3.2%-7%(car)-1%(car)-2.4%(car)-8%Growth then fall-1% to -1.8%Growth then fall-1.9% to -2.6%

Outcomes: patterns of demand(travel survey results)Mode shifte.g. replacement of trip by car with trip by bus, bike or foot +Destination/mode shifte.g. replacement of medium length car trips with shorter journeys by bus, bike or foot + Trip evaporation7% of reduction in car use from a net reduction in trips

Car driver trips and distance: variation in impact according to trip lengthLargest behaviour change seen in short trips, but largest reductions in DISTANCE from medium/ long distance trips

Chart1

0.220.02

0.140.1

0.10.23

0.060.19

0.030.47

% reduction in car driver trips (left axis)

proportion of total reduction in car driver distance (right axis)

distance band (km)

WTP overview

DarlingtonPeterboroughWorcester

workforce in the town34,00098,90049,648

employees covered by fully fledged WTP in May 2008377012,2855550

employees in companies with various travel initiatives in May 2008209,3451390

employees in companies that are considering a travel plan44509,6003562

employees in companies with a minimal travel plan29451,1164750

% of workforce covered by fully-fledged WTP11%12%11%fully-fledged travel plan

% of workforce in companies with various travel initiatives0%9%3%various travel initiatives

% of workforce in companies that are considering a travel plan13%10%7%considering a travel plan

% of workforce in companies with a minimal travel plan9%1%10%minimal travel plan

% of workforce in companies where there is no travel plan67%67%69%no travel plan


fully-fledged travel plan11%12%11%

some engagement in travel planning22%20%20%

no travel plan67%67%69%

Lynn's estimate, based on annual business inquiry data, and covers entire Peterborough unitary area

WTP overview

0.11088235290.21808823530.6710294118

0.12421638020.20284125380.672942366

0.11178698030.19541572670.6927972929

fully-fledged travel plan

some engagement in travel planning

no travel plan

% workforce

STP overview

% of total pupils at schools in the town


level A (active school travel plan)58%24%34%

level B (STP agreed and some school travel initiatives)9%36%47%

level B- (STP agreed but little evidence of activity)4%17%0%

level C (school contacted and starting to develop school travel work)27%0%18%

no engagement / no activity as yet2%23%0%

level C-0%13%0%

at schools with which there had been no engagement2%9%0%


active STP58%24%34%

STP agreed13%53%47%

no STP agreed29%23%18%

STP overview

0.5803798850.12830216140.2913179536

0.24349792690.5288729740.2276290991

0.34499366290.47294043090.1820659062

active STP

STP agreed

no STP agreed

% pupils

PTP overview


households targeted100%50%60%

households contacted69%41%49%

households receiving intervention materials45%22%26%

PTP overview

households targeted

households contacted

households receiving intervention materials

chg in work car

no. staff in year of most recent surveycars per 100 staff beforecars per 100 staff after% change%-point changetravel plan qualitynumber of cars 'before'number of cars 'after'change in no. of carschange in no. of cars

Royal Haskoning27582.566-20.0-16.5FF227182-45-139

Peterborough Primary Care Trust17082.569-16.4-13.5FF140117-23-113

Axiom Housing599178-14.3-13VT5446-8-58

Kiddicare1107061-12.9-9VT7767-10-45

Peterborough Regional College73378.568.5-12.7-10FF575502-73

Bauer Consumer Media5508473.5-12.5-10.5C462404-58-23

Peterborough City Council16407465.5-11.5-8.5FF12141074-139-13

VFM Services906762.5-6.7-4.5VT6056-4-10

Thorpewood Business Park250078.874.3-5.7-4.5VT19701858-113-8

Environment Agency3807874.5-4.5-3.5VT/C296283-13-8

Coca Cola12074.573-2.0-1.5?8988-2-7

Anglian Water5038078.5-1.9-1.5FF403395-8-4

Norwich and Peterborough Building Society4508583.5-1.8-1.5FF383376-7-2

Peterborough and Stamford NHS Hospital Trust360068.568.50.00FF2466246600

Perkins Engines270076.577.51.31C20662093272

Ideal Shopping Direct75078825.14FF585615308

Travelex55079.5845.74.5VT4374622525

Mencap70687916.211FF4855827

Peterborough Environment City Trust323643.520.87.5FF1214230

TOTAL for all organisations15282.12575.773.0-3.5-2.71156311152-410

TOTAL for FF organisations822373.670.5-4.2-3.160515796-255

TOTAL for VT or VT/C organisations368978.575.1-4.2-3.328952772-123

TOTAL for organisations which have achieved reductions7580.12578.571.9-8.4-6.659505448-502

TOTAL for organisations which have not achieved reductions770272.974.11.61.25613570592

unweighted mean (all orgs)75.471.7-5%-3.7

unweighted mean (successful orgs)78.971.4-10%-7.5

assumes staff numbers as in most recent survey i.e. approximates to number of cars if there had been no WTP

chg in work car

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

% change in cars per 100 staff

chg school summary

raw data in 1d Darl, 2d Pboro, 3d Worc worksheetsall, ranked A to Z

DarlingtonPeterboroughWorcesterall-100

-57-68-100-57-68

-45-64-49-45-64

-37-62-48-37-62

-30-61-29-30-61

-27-59-29-27-59

-27-46-28-27-57

-25-44-25-25-55

-20-37-24-20-53

-20-36-22-20-49

-13-34-21-13-48

-12-33-18-12-46

-11-29-17-11-45

-11-26-16-11-44

-7-26-15-7-41

-6-26-14-6-37

-6-26-14-6-37

-5-23-13-5-36

-5-20-13-5-34

-4-20-11-4-33

-3-19-10-3-33

-3-18-9-3-30

-0-17-8-0-29

3-16-33-29

3-16-13-29

3-16-13-28

6-1526-28

8-1348-27

9-1249-27

32-101432-26

59-72059-26

105-737105-26

-665-68-26

-4-64-25

-2-62-25

-2-61-24

-1-59-23

0-46-22

0-44-21

1-37-20

3-36-20

4-34-20

4-33-20

5-29-19

8-26-18

11-26-18

13-26-17

14-26-17

21-23-16

24-20-16

29-20-16

30-19-16

38-18-15

58-17-15

-55-16-14

-53-16-14

-41-16-13

-33-15-13

-28-13-13

-11-12-13

8-10-12

14-7-12

27-7-11

-6-11

-4-11

-2-11

-2-10

-1-10

0-9

0-8

1-7

3-7

4-7

4-6

5-6

8-6

11-5

13-5

14-4

21-4

24-3

29-3

30-3

38-2

58-2

-55-1

-53-1

-41-1

-33-0

-280

-110

81

142

273

-1003

-493

-483

-294

-294

-284

-254

-245

-226

-218

-188

-178

-169

-1511

-1413

-1414

-1314

-1314

-1120

-1021

-924

-827

-329

-130

-132

237

438

458

1459

2065

37105

65

this is the number of city centre office staff; this group was the main focus of both the travel plan and the surveys

ranked with largest cut in no. of cars first, to draw graph

-139.4

-112.5

-57.75

-45.375

-22.95

-13.3

-9.9

-7.67

-7.546875

-6.75

-4.05

-1.8

0

2.4

7.7

24.75

27

30

chg school summary

-100

-68.4669939989

-64.1304347826

-61.6925564068

-61.067961165

-59.2936802974

-56.5475014813

-55.3656220323

-52.6738283556

-49.0363850086

-48.1399631676

-46.1430855316

-44.7115384615

-43.9544625587

-40.6423667865

-37.0356920523

-36.9787446238

-35.9567640601

-34.4365642238

-33.1288343558

-33.0357142857

-29.8502236919

-29.3151293151

-29.1975308642

-28.9473684211

-28.3008658009

-28.1998980112

-26.5672588832

-26.5231209991

-26.4903329753

-26.2368158234

-25.9259259259

-25.5315232398

-25.0188964475

-24.8896103896

-24.2644266017

-23.3142079735

-21.6326530612

-20.6258890469

-20.2172096909

-20.0353107345

-19.7139229457

-19.709607698

-19.2713038241

-18.3521303258

-18.0376028202

-17.1961467514

-16.6666666667

-16.4705882353

-16.3431794597

-16.2274829601

-15.6722474376

-14.6326267476

-14.5180023229

-13.9508767832

-13.7438586666

-13.1867329047

-13.0718954248

-12.6649257834

-12.567132116

-11.8163205616

-11.5364097093

-11.4989444053

-11.3618350506

-10.787439976

-10.5995395856

-10.443952177

-10.0399126772

-9.4427973733

-7.976519337

-7.4094077537

-7.3310060298

-7.2793468667

-6.4758247513

-6.2598845121

-6.1258383903

-5.4664607301

-5.0806451613

-4.0692755156

-4.0296433534

-3.4710743802

-3.0671120559

-2.8383523711

-2.3143797938

-2.3136246787

-1.3963743263

-0.6276114655

-0.5947003914

-0.4845587285

0

0.2358175751

1.387755102

2.4617431803

2.6619883041

3.1633616619

3.1794728769

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schools

% change

chngs in car trips and dist

% reduction in car driver trips (left axis)proportion of total reduction in car driver distance (right axis)

Outcomes: who changed behaviour?men + women equallymost age groups (but 41-45 yrs & 61-65 yrs show less change)People at a transition point most susceptible:largest reductions: college students, job seekers, recently retiredlowest reductions: full-time and part-time workers and intensive car users (41-45 year olds)Car driver mode share for full-time workers fell by 5%, but contributed 40% of reduction in car driver trips

Which groups contributed most to the change in car driving?

Which journey purposes were most affected?Looking at reduction in total car driver distance (trips

Ingredient 1: Combination of hard + softIn the STTs, the largest changes took place: Where cycle infrastructure was improved (Darlington) Where bus services were improved (Peterborough)

In Scotland, after the first year of SCSP little behaviour change so far as infrastructure has not yet been sufficiently improved.

Ingredient 2: Smarter PLACES (SCSP)Need to pay attention to local culture and norms Not all initiatives suit all places (e.g. individualised marketing, cycling)

I would like to travel by car more oftenSmarter Choices, Smarter Places baseline study (2009)

Ingredient 3: Segmentation (SCSP)Target motivational and hard-to-reach groupsSmarter Choices, Smarter Places baseline study (2009)

Ingredient 4: Complementary measuresChange needs to take place at three levels:Individual incorporating values, attitudes, beliefs, social norms, identity and intentionsInterpersonal the relationship between individuals (trust, social networks)Community dynamics of structures and institutions (societal norms and culture; communications and the media)

This requires a multi-pronged attack a variety of synergistic measures and a sub-regional approach to foster a diffusion effect

Ingredient 5: Less focus on CO2? (SCSP)People should be allowed to use their cars as much as they like even if it damages the environmentSmarter Choices, Smarter Places baseline study (2009)

Ingredient 6: A trustworthy messengerA clear brand identity Remote from local government identity

If only it were this simple

Barriers to behaviour changeValuesEfficacyStatus and identitySocial normsPerceived controlAffective attitudesHABIT Choice

Anable, J. et al. (2006) An Evidence Base Review of Attitudes to Climate Change and Transport. for the DfT

INDIVIDUAL SUBJECTIVE

INDIVIDUAL OBJECTIVE

Values

Moral norms

Sense of responsibility

Perceived control

Self efficacy / agency

Denial

Instrumental attitudes

Affective attitudes

Identity and status

Heuristics

Knowledge

Habit

Personal capabilities

Actual resource constraints

COLLECTIVE SUBJECTIVE

COLLECTIVE OBJECTIVE

Social dilemmas

Group cultures/ shared norms

Trust in others and in government

Contextual/ situational factors

Communication / the media

Theories of behaviour changeSource: Anable, J.; Lane, B and Kelay, T. (2006) An Evidence Base Review of Attitudes to Climate Change and Transport. Report for the UK Department for Transport, London.

Individual Level

Interpersonal Level

Community/Network Level

The deficit model

Rational choice theory

The theory of planned behaviour

Norm activation theory

Values-beliefs-norms theory

Triandis theory of interpersonal behaviour

Social learning theory

Social capital theory

Diffusion of innovations

Stages of Change Models

1. Transtheoretical model (TTM)

2. Systems theory

Need to change context + attitudesTwo ways of thinking about changing behaviour:Influencing what people consciously think about (at all levels)Altering the context in which people act (The choice environment)

= need a combination of hard + soft

ConclusionsHard + Soft = Context + AttitudesTravel behaviour change means more than just mode shiftNot just short journeys principals of smarter choices should be applied to medium distance journey lenghtsWe know Smart Measures work, but:Need panel data: is it a few people changing a lot or a lot of people changing a little?Still dont know who responds in terms of attitudes and the psychological processes involved

*three medium-size English towns chosen to receive Government funding for expanded smarter choice programmesThis slide shows how the towns allocated their revenue spending between the different initiatives within the programme. Perhaps the first thing to notice is the broad similarities between them. All of them made personal travel planning a cornerstone of their programmes, and you can see that here. Its the cream slice and it accounts for the larger share of resources in all three towns.

The other thing to notice is that none of the towns spent a large amount on workplace or school travel planning thats the lilac and the maroon slices at the top.

*15mTimescalelaunches15m initiative*One of the main sources was a large household travel survey, conducted by Sustrans/Socialdata, which involved 4000 people in each town in both 2004 and 2008, giving a sample of over 25,000 people and 75,000 trips divided over 3 towns and 2 time periods. On the following slides, youll see a reference to weighted versus unweighted data this is just because there were different ways of processing the results from that survey, and we looked at both in most cases, it didnt really matter which one you used.We also had either manual or automatic counts of vehicles, cyclists, pedestrians and bus passengers, and,separately, there were results from travel surveys that had been carried out at schools and workplaces. To compare with that town-specific data, we also had national household survey data from the National Travel Survey, with special tabulations of data for medium-sized urban areas, and traffic count data for urban areas, collected and analysed to generate the National Road Traffic Estimates.All of these data sources measure slightly different things, and there are (different) concerns relating to reliability with all of them however, overall, when you put them all together, they do tell a broadly consistent story, and the fact that they do probably gives more confidence in the results than if you looked at any one data source in isolation.

*So to start with the household survey results - this graph gives a summary of the change in the actual number of trips done by different means per 100 people in each of the three towns between 2004 and 2008.And in all three towns, you can see the dark blue bars, which show reductions in the number of car trips; the dark green bars, which show increases in the number of walking trips; the paler green bars, which show increases in bus use in Worcester, and, more dramatically, Peterborough; and then the pale green bars, which show increases in cycling in all three, though particularly dramatic in Darlington.

*So now onto traffic and this slide is an attempt to summarise all of the data that we got about the impacts of the towns work on traffic and particularly car travel.The first table shows the results from the household surveys, compared with the National Travel survey as already highlighted, over the relevant period, as shown in the grey shaded box, there was a national fall in distance driven of 0.9%, but this was much smaller than the reductions reported by people living in the towns which, as shown in the green shaded box, were in the order of 5-7%.Meanwhile, the table on the right indicates the results obtained from traffic counts in the towns, both manual and automatic. Again, as shown in the grey box, nationally, data collected to produce the National Road Traffic Estimates indicates that traffic levels fell slightly by about 0.5% for car travel. However, the falls in the towns were all greater than that as shown in the last column, they were in the order of 2-3%, with particularly large reductions more like 7 or 8% in the inner areas of the towns.As you can see, the observed reductions on street in the order of 2 or 3% - are generally smaller than the reductions recorded in the household surveys for trips per person, and distance travelled. There are various explanations for this.

REASONS FOR THE GAP

Population growth (in Peterborough) and employment growth (in Darlington) Impacts in Worcester mainly on short tripsTowns not closed systems and non-resident traffic on major roads constituted perhaps half or more of traffic volumeResidents preferentially reduced car use for trips into inner areas perhaps because better served by bus Some induced traffic may also have occurred as relatively few locking in measures in the three towns

So to look more closely at the reasons for the gap between the household travel survey results for residents trips, and the observed traffic changes on-street In Peterborough, there was more than 6% population growth. In Darlington there was approximately 10% growth in employment. In both cases, then, even if trips per resident went down, there would have been new trips from new residents, or people commuting in, which would somewhat offset the reductions in car trips by existing residents.Meanwhile, in Worcester, the household surveys suggest that it was mainly the shortest trips that were affected meaning that the change in car driver distance by residents actually matched reasonably well with what was observed on street.As well as those major factors, it should be noted the towns are not closed systems and we had several results suggesting that non-resident traffic on major roads may have represented half or more of the total traffic volume so when traffic was measured on the major roads, its not surprising that you see smaller changes than you get in surveys of residents. Residents preferentially reduced car use for trips to inner areas, perhaps because these were the easiest to reach by bus, cycling or walking, with the result that there were higher traffic reductions at counters in the town centres than counters on the periphery, which is probably why the inner area counts match better with the household survey results than the overall totals. And also there may have been some induced traffic as there were relatively few locking in measures in the three towns. Given the complexity of the issues, Id just like to show you some of the key evidence which potentially suggests that a real traffic reduction did occur in each place.

Its also interesting to look at the outcomes from the household travel survey in terms of patterns of demand.

Tentatively, we can see evidence that suggests that the changes people were making in the three towns were more complex than simply switching mode from car to bus or bike.

There was also some destination switching that took place alongside modal shift so that, for example, a medium length car trip might be replaced by a shorter journey by bike or foot.

And there was some trip evaporation where a trip is no longer made at all. In fact 7% of the car use reduction appears to be from a net reduction in trips.

We can also see a difference in response to the smarter choice programmes in terms of journey distance.

The greatest behaviour change is for short trips, as shown by the green bars and the left axis. So, car driver trips of

what works in behaviour change? 28 june 2010, victoria quay, edinburgh

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